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Industrial Engineering Analytics EngineerSiri InfoSolutions • United States
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Industrial Engineering Analytics Engineer

Siri InfoSolutions
  • US
    United States
  • US
    United States
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Über

Job Title : Industrial Engineering Analytics Engineer Location: Pittsburg, PA Job Type :Fulltime/c2c Salary : $90k- $130k Key Responsibilities Develop and own integrated IE models that connect capacity, labor, material flow, PEFP, and cost (COGS) to support factory planning and operations Build and maintain capacity models (target vs. forecast vs. gated capacity), incorporating cycle time, OEE, yield losses, and bottleneck analysis Develop labor models to optimize headcount, utilization, and labor cost (LOH) across production systems Create and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost benefit analysis Lead COGS modeling, including labor, overhead, scrap, and process-driven cost components Develop and track scrap and yield models, quantifying cost impact and identifying improvement opportunities Design and maintain OEE models (availability, performance, quality) to drive operational efficiency and continuous improvement Perform buffer and WIP analysis to optimize inline and interline storage, reduce bottlenecks, and stabilize production flow Develop process flow diagrams (PFDs) and value stream maps to represent manufacturing systems and identify inefficiencies Integrate PFEP (Plan for Every Part) data into models to optimize material flow, storage, and line-side delivery strategies Support factory layout, site planning, and material flow decisions through data-driven insights and modeling Perform scenario analysis and sensitivity studies to evaluate production strategies and capacity expansion plans Utilize and/or develop factory simulation models (e.g., FlexSim, AnyLogic, Simio) to analyze throughput, bottlenecks, and system performance Support factory ramp-up, installation, and operational readiness through model validation and performance tracking Collaborate with cross-functional teams (Manufacturing, Operations, Supply Chain, Finance, Engineering) to align models with real-world constraints and business needs Translate complex analytical outputs into clear, executive-level insights and recommendations Collaborate with MES and Controls teams to integrate shop-floor data with IE models, ensuring accurate OEE measurement and enabling real-time, scalable dashboards for operational visibility and executive decision-making AI & Data Systems Introduce and implement AI-driven tools and platforms to enhance industrial engineering analytics and decision-making Design and manage scalable data models and data architecture for IE, capacity, labor, PFEP,and cost analytics Develop standardized systems, frameworks, and governance for data modeling, analytics, and reporting Automate data collection, validation, and reporting pipelines using AI and advanced analytics tools Enable predictive analytics and intelligent decision-making for capacity, throughput, and cost optimization Establish best practices for data quality, model standardization, and system integration across the organization
  • United States

Sprachkenntnisse

  • English
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